As well-known in the art, the statistical method of an automatic translation technique refers to a technique for solving the problem of translation ambiguity by automatically learning translation knowledge actually preferred by people through training data.
However, a parallel corpus used as learning data is utilized as lexicon-based sentence data. Thus, bilingual translation knowledge for transformation is relatively limited unless expressions formed by all combinations of words, which are substantially infinite, are constructed as learning data and applied. To statistically collect consistent tendencies of translation or learn the frequency of an expression, the learning of more than a certain amount of sentences using the corresponding expression is required.
Meanwhile, the pattern-based method can solve the data deficiency problem to a certain extent compared to a lexicon-based translation knowledge-based method by describing pattern data corresponding to a lexicon-based sentence to construct bilingual translation information thereof. However, there arises the problem of ambiguity of a translation result because a plurality of applicable patterns and translation knowledge can be generated.
As stated above, when automatic translation is performed using the statistics-based method or the pattern-based approach as the conventional automatic translation technique, each of the methods has a deficiency in solving the ambiguity of a translation result.